Image processing device, image processing method, photographic imaging apparatus, and recording device recording image processing program

ABSTRACT

An image processing device includes: a motion-vector computation unit that computes a motion vector between a base image and a reference image; a motion compensation unit that performs a motion compensation to align the reference image with the base image based on the motion vector; a contrast computation unit that computes a contrast value of a target pixel of the base image based on one of the base image and the reference image; a synthetic ratio computation unit that computes a synthetic ratio between: the target pixel for a synthesis processing in the base image; and a corresponding pixel corresponding to the target pixel in the reference image processed by the motion compensation, in response to the contrast value of the target pixel; and a synthesizing unit that synthesizes the target pixel of the base image and the corresponding pixel of the reference image based on the synthetic ratio.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Patent ApplicationNo. PCT/JP2011/79170, filed on Dec. 16, 2011, which claims the benefitof Japanese Patent Application No. JP 2011-031119, filed on Feb. 16,2011, which are incorporated by reference as if fully set forth.

TECHNICAL FIELD

The present invention relates to an image processing device, an imageprocessing method, a photographic imaging apparatus, and a recordingdevice recording an image processing program.

BACKGROUND ART

Known techniques for reducing an amount of noise of a moving imageinclude a cyclic noise reduction technique. This technique performsmotion compensation between an input frame image and a processedprevious frame image, and computes reliability of the motioncompensation related to each pixel based on differences from peripheralpixels. The input frame image (the current frame) and the previous frameimage are blended and synthesized in a blending synthetic ratio (amixing ratio) derived from a reliability, an amount of motion, and anestimated amount of noise (see Japanese Patent No. 4321626 and JapanesePatent Application Laid-open No. 2010-147986).

In recent years, a motion detection for each pixel by recording a movingimage at high image quality and high frame rate increases the circuitsize and the computation time. On the other hand, a motion compensationbased on a motion detection with discrete points reduces the circuitsize and the computation time. In this case, an error occurs in themotion detection. In a block matching method and similar method thatallow a high-speed motion detection, an error occurs in a motiondetection due to influences of, for example, lens distortion and rollingshutter. Additionally, an error occurs in a motion detection due to aninfluence of noise. Therefore, the known technique that reduces theamount of noise increases the synthetic ratio of the previous frameimage as the reliability of the motion compensation becomes higher, andreduces the synthetic ratio of the previous frame image as thereliability of the motion compensation becomes lower, so as to preventoccurrence of image lag and artifact during the blend synthesis. Itshould be noted that the reliability of the motion compensation can becomputed from an evaluation value for dissimilarity, for example, thesum of absolute difference (SAD) between the images processed by themotion compensation. The reliability increases as the sum of absolutedifference becomes smaller, and decreases as the sum of absolutedifference becomes larger.

SUMMARY OF INVENTION

According to an embodiment of the present invention, there is providedan image processing device for performing synthesis processing with abase image and at least one reference image to generate a syntheticimage with a small amount of noise at least compared with the baseimage. The image processing device includes: a motion-vector computationunit that computes a motion vector between the base image and thereference image; a motion compensation unit that performs a motioncompensation to align the reference image with the base image based onthe motion vector; a contrast computation unit that computes a contrastvalue of a target pixel for the synthesis processing in the base imagebased on one of the base image and the reference image; a syntheticratio computation unit that computes a synthetic ratio between: thetarget pixel of the base image; and a corresponding pixel correspondingto the target pixel in the reference image processed by the motioncompensation, in response to the contrast value of the target pixel; anda synthesizing unit that synthesizes the target pixel of the base imageand the corresponding pixel of the reference image based on thesynthetic ratio.

According to another embodiment to the present invention, there isprovided an image processing method for performing synthesis processingwith a base image and at least one reference image to generate asynthetic image with a small amount of noise at least compared with thebase image. The image processing method includes: computing a motionvector between the base image and the reference image; performing amotion compensation to align the reference image with the base imagebased on the motion vector; computing a contrast value of a target pixelfor the synthesis processing in the base image based on one of the baseimage and the reference image; computing a synthetic ratio between: thetarget pixel of the base image; and a corresponding pixel correspondingto the target pixel in the reference image processed by the motioncompensation, in response to the contrast value of the target pixel; andsynthesizing the target pixel of the base image and the correspondingpixel of the reference image based on the synthetic ratio.

According to further another embodiment of the present invention, thereis provided a computer-readable recording device having an imageprocessing program coded and recorded thereon in a computer readableformat, the image processing program performing synthesis processingwith a base image and at least one reference image to generate asynthetic image with a small amount of noise at least compared with thebase image, wherein the image processing program causes a computer toexecute a method comprising: a motion-vector computation step ofcomputing a motion vector between the base image and the referenceimage; a motion compensation step of performing a motion compensation toalign the reference image with the base image based on the motionvector; a contrast computation step of computing a contrast value of atarget pixel for the synthesis processing in the base image based on oneof the base image and the reference image; a synthetic ratio computationstep of computing a synthetic ratio between: the target pixel of thebase image; and a corresponding pixel corresponding to the target pixelin the reference image processed by the motion compensation,corresponding to the contrast value of the target pixel; and asynthesizing unit step of synthesizing the target pixel of the baseimage and the corresponding pixel of the reference image based on thesynthetic ratio.

The foregoing and additional features and characteristics of thisdisclosure will become more apparent from the following detaileddescription considered with the reference to the accompanying drawings.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an image processing deviceaccording to the present invention;

FIG. 2 is a sequence diagram illustrating a blend synthesis processingaccording to the present invention;

FIG. 3 is a flowchart illustrating a procedure of a reliabilitycomputation process according to a first embodiment;

FIG. 4A is a graph illustrating an exemplary method for correctingdissimilarity;

FIG. 4B is a graph illustrating another exemplary method for correctingdissimilarity;

FIG. 4C is a graph illustrating another exemplary method for correctingdissimilarity;

FIG. 5 is a graph illustrating a relationship between a reliability R ofa motion compensation and a blending synthetic ratio;

FIG. 6 is a flowchart illustrating a procedure of a reliabilitycomputation process according to a second embodiment;

FIG. 7 is an exemplary table for associating a contrast value with asize of a computational area of dissimilarity according to the secondembodiment;

FIG. 8 is a flowchart illustrating a procedure of a reliabilitycomputation process according to a third embodiment;

FIG. 9 is an exemplary table for associating a contrast value with astrength of a low-pass filter according to the third embodiment; and

FIG. 10 is a flowchart exemplarily illustrating a procedure of an imageprocessing program.

DESCRIPTION OF EMBODIMENTS First Embodiment

FIG. 1 illustrates a block configuration diagram of an image processingdevice according to a first embodiment. In this embodiment, the imageprocessing device is mounted on a photographic imaging apparatus. Thephotographic imaging apparatus is described as an example of electronicequipment such as a video camera and an electronic still camera.

The photographic imaging apparatus includes an image pickup unit 100 andan image processing device 200. The image pickup unit 100 for shootingan image functions as an image input unit for inputting an image (imagedata) to the image processing device 200. The image processing device200 outputs a noise-reduced image to the outside.

The image pickup unit 100 includes an imaging optical system, an imagingelement, an A/D converter circuit. The image processing device 200includes a motion-vector computation unit 101 (motion-vector computationmeans), a motion compensation unit 102 (motion compensation means), acontrast computation unit 103 (contrast computation means), areliability computation unit 104 (reliability computation means), asynthetic ratio computation unit 105 (synthetic ratio computationmeans), and a blend synthesis unit 106 (blend synthesis means). Itshould be noted that each unit (or all the units) of the imageprocessing device 200 described above may be constituted of a logiccircuit such as an ASIC and an FPGA. Alternatively, each unit (or allthe units) of the image processing device 200 described above may beconstituted of, for example, a memory for storing data, a memory forstoring a calculation program, and a central processing unit/a digitalsignal processor (CPU/DSP) for executing this calculation program.

Additionally, the image processing device 200 includes a frame memory107 (a storage unit). The frame memory 107 stores a current frame imagethat is shot and output to the frame memory 107 by the image pickup unit100 and a previous frame image output from the blend synthesis unit 106as pixel value data.

The previous frame image and the current frame image stored in the framememory 107 are input to the motion-vector computation unit 101, andrespectively used as a reference image and a base image (standardimage). Here, the “previous frame image” is an image that is output fromthe blend synthesis unit 106 and stored in the frame memory 107 in theprevious process of the image processing device 200. The “current frameimage” is an image (an image before synthesis) that is shot by the imagepickup unit 100 and targeted for blend synthesis in the current processof the image processing device 200.

The motion-vector computation unit 101 computes a motion vector betweentwo input frame images using a template matching method or similarmethod, and outputs the motion vector to the motion compensation unit102. The motion compensation unit 102 compensates the motion (thepositional deviation) such that the previous frame image as thereference image is aligned with the current frame image as the baseimage. Additionally, the motion compensation unit 102 cuts out a smallarea of the current frame image and a small area of the previous frameimage aligned with the current frame image. The small areas of theprevious frame image and the small area of the current frame image areassociated with each other, and respectively referred to also as areference area and a base area. The motion compensation unit 102determines a cut-out position of the small area of the previous frameimage based on the motion vector so as to cancel the motion vector. Thesmall area is an area that includes a target pixel targeted for theblend synthesis at the center and is a smaller area with a predeterminedsize compared with the entire image, for example, an area of 3×3 pixelsor 5×5 pixels.

The frame memory 107 stores pixel value data of the small area of thecurrent frame image (the base image) and the small area of the previousframe image (the reference image). The pixel value data is input to thecontrast computation unit 103. The contrast computation unit 103computes a contrast value CN of the target pixel targeted for blendsynthesis, and outputs the contrast value CN to the reliabilitycomputation unit 104.

The reliability computation unit 104 computes dissimilarity (such as theSum of Absolute Difference (SAD)) or similarity (such as the NormalizedCross-Correlation (NCC)) between the small area of the current frameimage and the small area of the previous frame image. Additionally, thereliability computation unit 104 corrects this dissimilarity orsimilarity in response to the contrast value CN. Furthermore, thereliability computation unit 104 computes a reliability R (that is, areliability R of the motion vector) of the motion compensation based onthe corrected dissimilarity or similarity, and outputs the reliability Rto the synthetic ratio computation unit 105. It should be noted that thesimilarity becomes smaller as the dissimilarity becomes larger.

The synthetic ratio computation unit 105 computes a blending syntheticratio of the target pixel (the center pixel of the small area) of thecurrent frame image and the corresponding pixel corresponding to thetarget pixel in the previous frame image, based on the input reliabilityR. The synthetic ratio computation unit 105 outputs the blendingsynthetic ratio to the blend synthesis unit 106. In the case where thesynthetic ratio of the corresponding pixel of the previous frame imageis assumed to be a, the synthetic ratio of the target pixel of thecurrent frame image becomes (1−α). The blend synthesis unit 106 blendsand synthesizes the target pixel and the corresponding pixel at thecalculated synthetic ratio as the synthesis processing. The blendsynthesis unit 106 outputs the result of the synthesis processing to theframe memory 107 for storage. As the blend synthesis, a weightedaddition or a weighted average is performed using the synthetic ratio ofthe target pixel and the corresponding pixel as a weight.

Subsequently, the blend synthesis is performed on all target pixels(that is, all pixels of the current frame image). The synthetic image inthe frame memory 107 is then output to a recording medium (a memorycard) or similar medium and recorded, or output to a display unit (suchas an LCD monitor) and displayed.

FIG. 2 illustrates a process sequence diagram according to the firstembodiment. During moving image shooting where a plurality of images isshot continuously, a first input image is directly used as an outputimage. When a second input image is shot, the stored first output image(the previous frame image) and the second input image (the current frameimage) are blended and synthesized to generate a synthetic image. Thissynthetic image is used as a second output image. As illustrated in FIG.2, blend synthesis is performed after third input image similarly to thesecond input image.

A description will be given of a method for computing a contrast in thecontrast computation unit 103. For example, the contrast computationunit 103 obtains an average value of luminance within the small areaincluding the target pixel among the luminances in the current frameimage, and computes a difference amount (an absolute value of thedifference) between the average value and a luminance of each pixelwithin the small area. The maximum difference amount is set to be acontrast value CN with respect to the target pixel. Alternatively, forexample, the contrast computation unit 103 may set the differencebetween the lowest luminance and the highest luminance within the smallarea including the target pixel among the luminances in the currentframe image as the contrast value CN with respect to the target pixel.In these two cases, the contrast value CN may take a value in a rangefrom 0 to 255.

Furthermore, for example, the contrast computation unit 103 may set thecontrast value CN with respect to the target pixel as follows. In thesmall area including the target pixel in the current frame image,filtering is performed on each pixel with a filter (such as adifferential filter, the Sobel filter, and the Laplacian filter) forextracting edges. A sum of the edge amounts within the small area isnormalized as the contrast value CN. In this case, the normalization maybe performed to have a value in a range from 0 to 255 on the same scaleof a contrast value CN generated by another method.

It should be noted that the luminance of the current frame image is usedin the above-described three methods for computing the contrast.However, a value that indicates a brightness of the pixel may be used.For example, a pixel value of G among the three primary colors RGB maybe used. While the contrast value is computed from the current frameimage, the contrast value may be computed using the small area includingthe corresponding pixel of the previous frame image. This is because thecorresponding pixel of the previous frame image is specified by themotion compensation. The corresponding pixel has a positioncorresponding to a position of the target pixel of the current frameimage (the base image) by the motion compensation.

A flowchart of FIG. 3 illustrates a procedure of a reliabilitycomputation process executed by the reliability computation unit 104. Inthe flow chart, a number with S denotes a step number.

First, in S11, the reliability computation unit 104 reads the pixelvalue data of the small area of the current frame image and the pixelvalue data of the small area of the previous frame image that isextracted by alignment from the frame memory 107. Subsequently, thereliability computation unit 104 computes the sum of absolute difference(SAD) as dissimilarity between both the small areas. Instead, thereliability computation unit 104 may compute the sum of squareddifference (SSD) of the pixel values as dissimilarity and the normalizedcross-correlation (NCC) as similarity.

In S12, the reliability computation unit 104 compares the contrast valueCN with a first threshold value TH₁ to determine whether or not the SAD(that is, the dissimilarity) needs to be corrected based on thecomparison result. In case where the contrast value CN is equal to orless than the first threshold value TH₁, the SAD does not need to becorrected. In the case where the contrast value CN is larger the firstthreshold value TH₁, the SAD needs to be corrected. In the case wherethe SAD needs to be corrected, the routine advances to S13 and S14. Inthe case where the case where the SAD does not need to be corrected, theroutine advances to S15. In S13, the reliability computation unit 104corrects the SAD (the dissimilarity) in response the contrast value CN.The correcting method will be described later.

In S14, the reliability computation unit 104 computes the reliability Rof the motion compensation based on the corrected SAD (the SAD after thecorrection). In S15, the reliability computation unit 104 computes thereliability R of the motion compensation based on the SAD (the SADcalculated in S11) that is not corrected. It should be noted that in thecase where the SAD and the SSD are used as the dissimilarity, thereliability R is computed such that the reliability R becomes higher asthe dissimilarity becomes smaller and becomes lower as the dissimilaritybecomes larger. For example, the reliability R can be calculated using afunction where the value becomes smaller as the dissimilarity becomeslarger. It should be noted that in the case where the normalizedcross-correlation (NCC) is used as the similarity, the reliabilitycomputation unit 104 computes the reliability R that becomes higher asthe similarity becomes larger and becomes lower as the similaritybecomes smaller.

Thus, the reliability computation unit 104 computes the reliability R inresponse to the contrast of the target pixel by the reliabilitycomputation process from S11 to S14. Therefore, the synthetic ratiocomputation unit 105 calculates the synthetic ratio in response to thereliability R, thus obtaining the synthetic ratio based on the contrastof the target pixel.

A method for correcting the SAD (the dissimilarity) will be described inconjunction with FIGS. 4A to 4C. For example, a gain value GN iscalculated in response to the contrast value CN. A value obtained bymultiplying the SAD calculated in S11 by the gain value as a correctionamount may be the corrected SAD (the SAD after the correction).Alternatively, an offset value VF is calculated in response to thecontrast value CN. A value obtained by subtracting the offset value as acorrection amount from the SAD calculated in S11 may be the correctedSAD (the SAD after the correction). It should be noted that in the casewhere the reliability computation unit 104 computes the reliability R ofthe motion compensation based on the corrected NCC (the NCC after thecorrection), a value obtained by dividing the NCC calculated in S11 bythe gain value or a value obtained by adding the offset value to the NCCcalculated in S11 may be the corrected NCC (the NCC after thecorrection).

In Correction example 1 of FIG. 4A, the SAD is corrected bymultiplication of the gain value. In the case where the contrast valueCN is equal to or less than the first threshold value TH₁, the gainvalue is a value (the first correction amount) independent from thecontrast value. In this embodiment, the gain value of 1.0 is equivalentto no correction. In the case where the contrast value CN is larger thanthe first threshold value TH₁, the gain value becomes smaller as thecontrast value CN becomes higher. As illustrated in FIG. 4A, the gainvalue is determined based on the contrast value by a function, a map, ora table for associating the gain value with the contrast value. Thevalue obtained by multiplying the SAD calculated in S11 by the gainvalue is set to the SAD after the correction.

In Correction example 2 of FIG. 4B, the SAD is corrected bymultiplication of the gain value. In the case where the contrast valueCN is equal to or less than a first threshold value TH₁, the gain valueis a value (the first correction amount) independent from the contrastvalue. In this embodiment, the gain value of 1.0 is equivalent to nocorrection. In the case where the contrast value CN is in a range fromthe first threshold value TH₁ to a second threshold value TH₂, the gainvalue becomes smaller as the contrast value CN becomes higher. In thecase where the contrast value CN is equal to or more than the secondthreshold value TH₂, the gain value is a constant value (a secondcorrection amount) independent from the contrast value. As illustratedin FIG. 4B, the gain value is determined based on the contrast value bya function, a map, or a table for associating the gain value with thecontrast value. The value obtained by multiplying the SAD calculated inS11 by the gain value is set to the SAD after the correction.

In Correction example 3 of FIG. 4C, the SAD is corrected by subtractionof the offset value. In the case where the contrast value CN is equal toor less than the first threshold value TH₁, the offset value is a value(the first correction amount) independent from the contrast value. Inthis embodiment, the contrast value is zero. This is equivalent to nocorrection. In the case where the contrast value CN is in a range fromthe first threshold value TH₁ to the second threshold value TH₂, theoffset value becomes larger as the contrast becomes higher. In the casewhere the contrast value CN is equal to or more than the secondthreshold value TH₂, the offset value is a constant value (the secondcorrection amount) independent from the contrast value. As illustratedin FIG. 4C, the offset value is determined based on the contrast valueby a function, a map, or a table for associating the offset value withthe contrast value. The value obtained by subtracting the offset valuefrom the SAD calculated in S11 is set to the SAD after the correction.

It should be noted that even in the case where correction is performedwith the contrast value CN equal to or less than the first thresholdvalue TH₁ (that is, in the case where the gain value is not 1.0 or inthe case where the offset value is not zero), the steps of S12 and S15are skipped. In each of Correction examples 1 to 3, the first thresholdvalue TH₁ may have a different value. In each of correction examples 2and 3, the second threshold value TH₂ may have a different value.

FIG. 5 illustrates a relationship between the reliability R and theblending synthetic ratio. As illustrated in FIG. 5, the synthetic ratiocomputation unit 105 determines the synthetic ratio α of thecorresponding pixel of the previous frame image and the synthetic ratio(1−α) of the target pixel of the current frame image based on thereliability R. As illustrated by the solid line in FIG. 5, the syntheticratio α of the previous frame image becomes smaller as the reliability Rbecomes lower. As illustrated by the dashed line in FIG. 5, thesynthetic ratio (1−α) of the current frame image becomes larger as thereliability R becomes lower. The blend synthesis unit 106 blends andsynthesizes the target pixel of the current frame image and thecorresponding pixel of the previous frame image at the determinedsynthetic ratio. The blend synthesis unit 106 sets an image where allpixels of the current frame image are processed by image processing upto the blend synthesis as an output image with respect to the currentframe image. The frame memory 107 stores this output image as previousframe image used in the next frame processing.

It should be noted that in the first embodiment described above, thereliability computation unit 104 computes the reliability R based on tothe contrast of the target pixel. Therefore, the synthetic ratiocomputation unit 105, which computes the synthetic ratio from thereliability R, can indirectly compute the synthetic ratio in response tothe contrast of the target pixel. Alternatively, the reliabilitycomputation unit 104 may compute the reliability R independently of thecontrast without correction of the SAD. The synthetic ratio computationunit 105 may compute the synthetic ratio from the reliability R.Subsequently, the synthetic ratio may be corrected directly in responseto the contrast value CN. Further, the synthetic ratio may be obtainednot for each pixel but for each area of the image.

(Operation and Advantageous Effects)

Next, operation and advantageous effects of the first embodiment will bedescribed. The contrast computation unit 103 computes the contrast valueof the target pixel targeted for the synthesis processing in the baseimage (the current frame image) from the base image or the referenceimage (the previous frame image). The synthetic ratio computation unit105 computes the synthetic ratio of the target pixel of the base imageand the corresponding pixel corresponding to the target pixel in thereference image processed by the motion compensation, in response to thecontrast value of the target pixel. The blend synthesis unit 106 blendsand synthesizes the target pixel of the base image and the correspondingpixel of the reference image based on the computed synthetic ratio. Thisprevents a situation where an influence of a motion compensation erroron the synthetic ratio differs depending on the contrast. This avoidssway of the moving image in a motion detection accuracy where the motioncompensation error is generated, and reduces the amount of noise atleast compared with the base image.

The reliability computation unit 104 computes the reliability of themotion compensation for the target pixel in response to the contrastvalue of the target pixel. The synthetic ratio computation unit 105computes the synthetic ratio in response to the reliability.Accordingly, use of the reliability of the motion compensation inresponse to the contrast value appropriately prevents a situation wherethe influence of the motion compensation error on the synthetic ratiodiffers depending on the contrast. For example, in the case where thereliability is low, this improves the image quality of the image outputfrom the image processing device by reducing the synthetic ratio of thecorresponding pixel of the reference image (the previous frame image).

The reliability computation unit 104 computes dissimilarity orsimilarity between the base area including the target pixel of the baseimage and the reference area corresponding to the base area within thereference image processed by the motion compensation, so as to performcorrection as follows. The computed dissimilarity is reduced or thecomputed similarity is increased in response to the contrast value ofthe target pixel. The reliability computation unit 104 calculates thereliability such that the reliability becomes higher as the correcteddissimilarity becomes smaller or the corrected similarity becomeslarger. In the case of the high contrast, the dissimilarity or thesimilarity becomes sensitive to the motion compensation error. However,the reliability is obtained based on the dissimilarity or the similaritycorrected in response to the contrast value. This prevents the motioncompensation error from considerably affecting the synthetic ratio in ahigh-contrast area of the image.

In the case where the contrast value of the target pixel is higher thanthe first threshold value TH₁, the reliability computation unit 104 mayperform correction such that the dissimilarity is reduced or thesimilarity is increased as the contrast value becomes higher. Thisappropriately prevents the motion compensation error from considerablyaffecting the synthetic ratio in the high-contrast area of the image. Inthe case where the contrast value of the target pixel is equal to ormore than the second threshold value TH₂, which is larger than the firstthreshold value, the dissimilarity or the similarity may be correctedwith the correction amount independent from the contrast value. Thisprevents excessively high synthetic ratio α of the reference image (theprevious frame image) by excessive reduction of the dissimilarity (byexcessive increase of the similarity) in the high-contrast area of theimage.

Second Embodiment

A flowchart in FIG. 6 illustrates a procedure of the reliabilitycomputation process executed by the reliability computation unit 104according to a second embodiment. The configuration other than thereliability computation process is similar to the configuration of thefirst embodiment, and is not explained in order to avoid duplications ofdescriptions. In the first embodiment, the reliability computation unit104 computes the dissimilarity (such as the SAD) (or similarity) betweenthe small area of the current frame image and the small area of theprevious frame image, and corrects the computed dissimilarity (orsimilarity) based on the contrast value. On the other hand, in thesecond embodiment, the reliability computation unit 104 does not correctthe computed dissimilarity (or similarity), but changes a size of acomputational area (the small area) for computing the dissimilarity (orsimilarity) in response to the contrast value. The computational area isan area that has the target pixel at the center. The reliabilitycomputation unit 104 cuts out a computational area (the base area) fordissimilarity of the current frame image (the base image) and acomputational area (the reference area) for dissimilarity of theprevious frame image (the reference image) to compute the dissimilarity(or similarity). Both the computational areas correspond to each otherby the motion compensation.

In S21, the reliability computation unit 104 discretizes the contrastvalue CN computed by the contrast computation unit 103. For example, thereliability computation unit 104 may divide the contrast value by aconstant value and round the division down (or up) to the nearest wholenumber so as to set the rounded value as the discretized contrast value.For example, in the case where the contrast value has a range from 0 to255, the contrast value is divided by a constant value of 64.Alternatively, the reliability computation unit 104 may performdiscretization by division with a constant value only in the case of thecontrast value within a certain range and perform differentdiscretization while associating respective constant values in the casewhere the contrast value is a value equal to or less than the range andin the case where the contrast value is a value equal to or more thanthe range.

In S22, the reliability computation unit 104 determines the size of thecomputational area for computing the dissimilarity corresponding to thediscretized contrast value. Accordingly, one size of the computationalarea corresponds to a range of the original contrast values before thediscretization. The size of the computational area for dissimilaritybecomes larger as the contrast value becomes higher. It should be notedthat a method for determining the size of the computational area will bedescribed later.

In S23, the reliability computation unit 104 computes the sum ofabsolute difference (SAD) of the pixel values as the dissimilaritybetween the respective computational areas of the current frame imageand the previous frame image. Instead, the reliability computation unit104 may compute the sum of squared difference (SSD) of the pixel valuesas the dissimilarity and compute the normalized cross-correlation (NCC)as the similarity.

In S24, the reliability computation unit 104 computes the reliability Rfrom the computed SAD. It should be noted that since the SAD as a sum islikely to become a larger value as the size of the computational areabecomes larger, the reliability R may be computed from a value obtainedby dividing the SAD by the number of pixels in the computational area.In the case where the dissimilarity is estimated by the SAD and the SSD,the reliability R is computed to be higher as the dissimilarity becomessmaller and to be lower as the dissimilarity becomes larger. Thereliability computation unit 104 computes the reliability R in responseto the contrast of the target pixel. Therefore, the synthetic ratiocomputation unit 105, which computes the synthetic ratio from thereliability R, can indirectly compute the synthetic ratio in response tothe contrast of the target pixel.

FIG. 7 illustrates an exemplary table for associating the discretizedcontrast value with the size of the computational area for dissimilarity(or similarity). FIG. 7 illustrates an example where the discretizedcontrast takes 0 to 3. The size of the computational area fordissimilarity (or similarity) becomes larger as the contrast valuebecomes higher. The reliability computation unit 104 refers to thistable to determine the size of the computational area. In the case wherethe discretized contrast is 0, 1, 2, or 3, the size of the computationalarea for dissimilarity (or similarity) becomes an area of 3×3 pixels,5×5 pixels, 7×7 pixels, or 9×9 pixels.

According to the second embodiment, as the contrast value of the targetpixel becomes higher, the reliability computation unit 104 sets largersizes of: the base area (the computational area of the base image)including the target pixel of the base image; and the reference area(the computational area of the reference image) corresponding to thebase area within the reference image processed by the motioncompensation, and computes the dissimilarity (or similarity) between thebase area and the reference area. Therefore, even in the case where thenoise and the motion compensation error occur at an acceptable level,this prevents extremely high dissimilarity such as the SAD (andextremely low similarity) in a portion of the image with a high contrastvalue. This reduces the influence of the motion compensation error onthe dissimilarity (or similarity) in the portion of the image with ahigh contrast value, and eventually with respect to the synthetic ratiocomputed from the reliability.

Third Embodiment

A flowchart in FIG. 8 illustrates a procedure of the reliabilitycomputation process executed by the reliability computation unit 104according to a third embodiment. The configuration other than thereliability computation process is similar to the configuration of thefirst embodiment, and is not explained in order to avoid duplications ofdescriptions. In the first embodiment, the reliability computation unit104 computes the dissimilarity (such as the SAD) (or similarity) betweenthe small area of the current frame image and the small area of theprevious frame image, and corrects the computed dissimilarity (orsimilarity) based on the contrast value. However, in the thirdembodiment, the reliability computation unit 104 does not correct thecomputed dissimilarity (or similarity), but filters a computational area(the base area) for dissimilarity of the current frame image (the baseimage) and a computational area (the reference area) for dissimilarityof the previous frame image (the reference image) using a low-passfilter for removing high spatial-frequency components before computingthe dissimilarity (or similarity). The strength of the low-pass filterfor filtering both the computational areas is changed in response to thecontrast value.

In S31, the reliability computation unit 104 discretizes the contrastvalue CN computed by the contrast computation unit 103 similarly to S21.In S32, the reliability computation unit 104 determines the strength ofthe low-pass filter for filtering the computational area fordissimilarity based on the discretized contrast value. Accordingly, onestrength of the low-pass filter corresponds to a certain range of theoriginal contrast values before the discretization.

In S33, the reliability computation unit 104 performs filtering on therespective computational areas of the previous frame image and thecurrent frame image with the determined strength of the low-pass filter.In S34, the reliability computation unit 104 computes the sum ofabsolute difference (SAD) of the pixel values as the dissimilaritybetween the respective computational areas of the current frame imageand the previous frame image after filtering. Instead, the reliabilitycomputation unit 104 may compute the sum of squared difference (SSD) ofthe pixel values as the dissimilarity and compute the normalizedcross-correlation (NCC) as the similarity.

In S35, the reliability computation unit 104 computes the reliability Rfrom the computed SAD. In the case where the dissimilarity is estimatedby the SAD and the SSD, the reliability R is computed to be higher asthe dissimilarity becomes smaller and to be lower as the dissimilaritybecomes larger. The reliability computation unit 104 computes thereliability R in response to the contrast of the target pixel.Therefore, the synthetic ratio computation unit 105, which computes thesynthetic ratio from the reliability R, can indirectly compute thesynthetic ratio in response to the contrast of the target pixel.

FIG. 9 illustrates an exemplary table for associating the discretizedcontrast value with the strength of the low-pass filter. FIG. 9illustrates an example where the discretized contrast takes 0 to 3. Thestrength of the low-pass filter becomes larger as the contrast becomeshigher. The reliability computation unit 104 refers to this table todetermine the strength of the low-pass filter. In the case where thediscretized contrast is 0, the low-pass filter process is not performed.In the case where the discretized contrast is 1, the strength of thelow-pass filter is low. In the case where the discretized contrast is 2,the strength of the low-pass filter is medium. In the case where thediscretized contrast is 3, the strength of the low-pass filter is high.

According to the third embodiment, the reliability computation unit 104filters: the base area (the computational area of the base image)including the target pixel of the base image; and the reference area(the computational area of the reference image) corresponding to thebase area within the reference image processed by the motioncompensation using the low-pass filter, and computes the dissimilarity(or similarity) between the base area and the reference area afterfiltering with the low-pass filter. Therefore, even in the case wherethe noise and the motion compensation error occur at an acceptablelevel, setting a higher strength of the low-pass filter as the contrastvalue becomes higher prevents extremely high dissimilarity such as theSAD (and extremely low similarity). This reduces the influence of themotion compensation error on the dissimilarity (or similarity), andeventually on the synthetic ratio computed form the reliability.Additionally, this configuration changes the strength of the low-passfilter, thus facilitating the implementation.

Other Embodiments

Although it is premised that the image processing device is processed byhardware in the respective embodiments mentioned above, the imageprocessing device is not necessarily processed by such a configuration.For example, a configuration is also possible where processing isperformed by software in a different manner. In this case, the imageprocessing device corresponds to a computer, and includes a CPU, a mainmemory such as a RAM that stores image data, and a computer-readablerecording device (or a non-transitory storage medium) on which a programfor realizing all or part of the above mentioned image processing isencoded in a computer-readable format and stored. Here, this program iscalled an image processing program. The CPU reads out the imageprocessing program stored on the above-mentioned storage medium andperforms image data processing and computing processing, realizingsimilar processing to that of the above mentioned image processingdevice.

Here, the computer-readable recording device (or a non-transitorystorage medium) refers to a magnetic disk, a magneto-optical disk, aCD-ROM, a DVD-ROM, a semiconductor memory, and similar recording device.This image processing program may be distributed to a computer through acommunication line and the computer receiving this distribution mayexecute the image processing program.

A flowchart in FIG. 10 illustrates an exemplary image processing programexecuted by the image processing device (the computer). In step S100,the image processing device reads image data (each frame of a movingimage) recorded in the recording medium such as a memory card. Theprocesses performed in steps S101 to S106 of FIG. 10 correspond torespective processes performed by the units 101 to 106 of FIG. 1.

While embodiments of the present invention have been described, thepresent invention may be variously changed or modified without departingfrom the scope or spirit of the present invention. Those skilled in theart would appreciate that such changes and modifications areincorporated into the scope of the invention and equivalents thereof asapparent from the appended claims.

What is claimed is:
 1. An image processing device for performingsynthesis processing with a base image and at least one reference imageto generate a synthetic image with a smaller amount of noise than thebase image, the image processing device comprising: a motion-vectorcomputation unit that computes a motion vector between the base imageand the reference image; a motion compensation unit that performs amotion compensation to align the reference image with the base imagebased on the motion vector; a contrast computation unit that computes acontrast value of a target pixel for the synthesis processing in thebase image based on one of the base image and the reference image; asynthetic ratio computation unit that computes a synthetic ratio betweenthe target pixel of the base image and a corresponding pixelcorresponding to the target pixel in the reference image processed bythe motion compensation, in response to the contrast value computed bythe contrast computation unit of the target pixel; and a synthesizingunit that synthesizes the target pixel of the base image and thecorresponding pixel of the reference image based on the synthetic ratio;wherein the contrast computation unit, within an area including thetarget pixel, computes a maximum value of a difference between anaverage value of one of luminance and brightness within the area, andone of luminance and brightness of each pixel, as the contrast value ofthe target pixel.
 2. A photographic imaging apparatus comprising theimage processing device according to claim
 1. 3. An image processingdevice for performing synthesis processing with a base image and atleast one reference image to generate a synthetic image with a smalleramount of noise than the base image, the image processing devicecomprising: a motion-vector computation unit that computes a motionvector between the base image and the reference image; a motioncompensation unit that performs a motion compensation to align thereference image with the base image based on the motion vector; acontrast computation unit that computes a contrast value of a targetpixel for the synthesis processing in the base image based on one of thebase image and the reference image; a synthetic ratio computation unitthat computes a synthetic ratio between the target pixel of the baseimage and a corresponding pixel corresponding to the target pixel in thereference image processed by the motion compensation, in response to thecontrast value computed by the contrast computation unit of the targetpixel; a synthesizing unit that synthesizes the target pixel of the baseimage and the corresponding pixel of the reference image based on thesynthetic ratio; and a reliability computation unit that computes areliability of the motion compensation for the target pixel in responseto the contrast value computed by the contrast computation unit of thetarget pixel; wherein the synthetic ratio computation unit computes thesynthetic ratio in response to the reliability computed by thereliability computational unit; and wherein the reliability computationunit: computes one of a dissimilarity and a similarity between a basearea including the target pixel of the base image, and a reference areacorresponding to the base area within the reference image processed bythe motion compensation; performs one of a correction to reduce thecomputed dissimilarity and a correction to increase the computedsimilarity, in response to the contrast value computed by the contrastcomputation unit of the target pixel; calculates the reliability suchthat the reliability becomes higher as the corrected dissimilaritybecomes smaller or as the corrected similarity becomes larger; performsone of a correction such that the dissimilarity is reduced more or thesimilarity is increased more as the contrast value of the target pixelbecomes higher, when the contrast value of the target pixel is within arange from a first threshold value to a second threshold value; andcorrects one of the dissimilarity and the similarity with a secondcorrection amount independent from the contrast value, when the contrastvalue of the target pixel is equal to or more than the second thresholdvalue.
 4. A photographic imaging apparatus comprising the imageprocessing device according to claim
 3. 5. An image processing devicefor performing synthesis processing with a base image and at least onereference image to generate a synthetic image with a smaller amount ofnoise than the base image, the image processing device comprising: amotion-vector computation unit that computes a motion vector between thebase image and the reference image; a motion compensation unit thatperforms a motion compensation to align the reference image with thebase image based on the motion vector; a contrast computation unit thatcomputes a contrast value of a target pixel for the synthesis processingin the base image based on one of the base image and the referenceimage; a synthetic ratio computation unit that computes a syntheticratio between the target pixel of the base image and a correspondingpixel corresponding to the target pixel in the reference image processedby the motion compensation, in response to the contrast value computedby the contrast computation unit of the target pixel; a synthesizingunit that synthesizes the target pixel of the base image and thecorresponding pixel of the reference image based on the synthetic ratio;and a reliability computation unit that computes a reliability of themotion compensation for the target pixel in response to the contrastvalue computed by the contrast computation unit of the target pixel;wherein the synthetic ratio computation unit computes the syntheticratio in response to the reliability computed by the reliabilitycomputational unit; and wherein the reliability computation unit: setsrespective larger sizes of a base area including the target pixel in thebase image and a reference area corresponding to the base area withinthe reference image processed by the motion compensation, as thecontrast value of the target pixel becomes higher; computes one of adissimilarity and a similarity between the base area and the referencearea; and calculates the reliability such that the reliability becomeshigher as the computed dissimilarity becomes smaller or as the computedsimilarity becomes larger.
 6. A photographic imaging apparatuscomprising the image processing device according to claim
 5. 7. An imageprocessing device for performing synthesis processing with a base imageand at least one reference image to generate a synthetic image with asmaller amount of noise than the base image, the image processing devicecomprising: a motion-vector computation unit that computes a motionvector between the base image and the reference image; a motioncompensation unit that performs a motion compensation to align thereference image with the base image based on the motion vector; acontrast computation unit that computes a contrast value of a targetpixel for the synthesis processing in the base image based on one of thebase image and the reference image; a synthetic ratio computation unitthat computes a synthetic ratio between the target pixel of the baseimage and a corresponding pixel corresponding to the target pixel in thereference image processed by the motion compensation, in response to thecontrast value computed by the contrast computation unit of the targetpixel; a synthesizing unit that synthesizes the target pixel of the baseimage and the corresponding pixel of the reference image based on thesynthetic ratio; and a reliability computation unit that computes areliability of the motion compensation for the target pixel in responseto the contrast value computed by the contrast computation unit of thetarget pixel; wherein the synthetic ratio computation unit computes thesynthetic ratio in response to the reliability computed by thereliability computational unit; and wherein the reliability computationunit: filters a base area and a reference area with a low-pass filter,the base area including the target pixel of the base image, and thereference area corresponding to the base area within the reference imageprocessed by the motion compensation; computes one of a dissimilarityand a similarity between the base area and the reference area afterfiltering with the low-pass filter; calculates the reliability such thatthe reliability becomes higher as the computed dissimilarity becomessmaller or as the computed similarity becomes larger; and sets a higherstrength of the low-pass filter as the contrast value becomes higher. 8.A photographic imaging apparatus comprising the image processing deviceaccording to claim
 7. 9. An image processing method of an imageprocessing device for performing synthesis processing with a base imageand at least one reference image to generate a synthetic image with asmaller amount of noise than the base image, the image processing methodcomprising: computing a motion vector between the base image and thereference image; performing a motion compensation to align the referenceimage with the base image based on the motion vector; computing acontrast value of a target pixel for the synthesis processing in thebase image based on one of the base image and the reference image;computing a synthetic ratio between the target pixel of the base imageand a corresponding pixel corresponding to the target pixel in theprocessed reference image, in response to the computed contrast value ofthe target pixel; and synthesizing the target pixel of the base imageand the corresponding pixel of the reference image based on thesynthetic ratio; wherein computing the contrast value of the targetpixel comprises, within an area including the target pixel, computing amaximum value of a difference between an average value of one ofluminance and brightness within the area, and one of luminance andbrightness of each pixel, as the contrast value of the target pixel. 10.An image processing method of an image processing device for performingsynthesis processing with a base image and at least one reference imageto generate a synthetic image with a smaller amount of noise than thebase image, the image processing method comprising: computing a motionvector between the base image and the reference image; performing amotion compensation to align the reference image with the base imagebased on the motion vector; computing a contrast value of a target pixelfor the synthesis processing in the base image based on one of the baseimage and the reference image; computing a synthetic ratio between thetarget pixel of the base image and a corresponding pixel correspondingto the target pixel in the processed reference image, in response to thecomputed contrast value of the target pixel; synthesizing the targetpixel of the base image and the corresponding pixel of the referenceimage based on the synthetic ratio; and computing a reliability of themotion compensation for the target pixel in response to the computedcontrast value of the target pixel; wherein the synthetic ratio iscomputed in response to the computed reliability; and wherein computingthe reliability comprises: computing one of a dissimilarity and asimilarity between a base area including the target pixel of the baseimage, and a reference area corresponding to the base area within thereference image processed by the motion compensation, performing one ofa correction to reduce the computed dissimilarity and a correction toincrease the computed similarity, in response to the computed contrastvalue of the target pixel; and calculating the reliability such that thereliability becomes higher as the corrected dissimilarity becomessmaller or as the corrected similarity becomes larger; whereincorrection is performed such that one of the dissimilarity is reducedmore or the similarity is increased more as the contrast value of thetarget pixel becomes higher, when the contrast value of the target pixelis within a range from a first threshold value to a second thresholdvalue; and wherein correction is performed such that one of thedissimilarity and the similarity is corrected with a second correctionamount independent from the contrast value, when the contrast value ofthe target pixel is equal to or more than the second threshold value.11. An image processing method of an image processing device forperforming synthesis processing with a base image and at least onereference image to generate a synthetic image with a smaller amount ofnoise than the base image, the image processing method comprising:computing a motion vector between the base image and the referenceimage; performing a motion compensation to align the reference imagewith the base image based on the motion vector; computing a contrastvalue of a target pixel for the synthesis processing in the base imagebased on one of the base image and the reference image; computing asynthetic ratio between the target pixel of the base image and acorresponding pixel corresponding to the target pixel in the processedreference image, in response to the computed contrast value of thetarget pixel; synthesizing the target pixel of the base image and thecorresponding pixel of the reference image based on the synthetic ratio;and computing a reliability of the motion compensation for the targetpixel in response to the computed contrast value of the target pixel;wherein the synthetic ratio is computed in response to the computedreliability; and wherein computing the reliability comprises: settingrespective larger sizes of a base area including the target pixel in thebase image and a reference area corresponding to the base area withinthe reference image processed by the motion compensation, as thecontrast value of the target pixel becomes higher, computing one of adissimilarity and a similarity between the base area and the referencearea, and calculating the reliability such that the reliability becomeshigher as the computed dissimilarity becomes smaller or as the computedsimilarity becomes larger.
 12. An image processing method of an imageprocessing device for performing synthesis processing with a base imageand at least one reference image to generate a synthetic image with asmaller amount of noise than the base image, the image processing methodcomprising: computing a motion vector between the base image and thereference image; performing a motion compensation to align the referenceimage with the base image based on the motion vector; computing acontrast value of a target pixel for the synthesis processing in thebase image based on one of the base image and the reference image;computing a synthetic ratio between the target pixel of the base imageand a corresponding pixel corresponding to the target pixel in theprocessed reference image, in response to the computed contrast value ofthe target pixel; synthesizing the target pixel of the base image andthe corresponding pixel of the reference image based on the syntheticratio; and computing a reliability of the motion compensation for thetarget pixel in response to the computed contrast value of the targetpixel; wherein the synthetic ratio is computed in response to thecomputed reliability; and wherein computing the reliability comprises:filtering a base area and a reference area with a low-pass filter, thebase area including the target pixel of the base image, and thereference area corresponding to the base area within the reference imageprocessed by the motion compensation; computing one of a dissimilarityand a similarity between the base area and the reference area afterfiltering with the low-pass filter; calculating the reliability suchthat the reliability becomes higher as the computed dissimilaritybecomes smaller or as the computed similarity becomes larger; andsetting a higher strength of the low-pass filter as the contrast valuebecomes higher.
 13. A computer-readable recording device having an imageprocessing program coded and recorded thereon in a computer-readableformat for controlling an image processing device to perform synthesisprocessing with a base image and at least one reference image togenerate a synthetic image with a smaller amount of noise than the baseimage, said program controlling the image processing device to performoperations comprising: computing a motion vector between the base imageand the reference image; performing a motion compensation to align thereference image with the base image based on the motion vector;computing a contrast value of a target pixel for the synthesisprocessing in the base image based on one of the base image and thereference image; computing a synthetic ratio between the target pixel ofthe base image and a corresponding pixel corresponding to the targetpixel in the processed reference image, in response to the computedcontrast value of the target pixel; and synthesizing the target pixel ofthe base image and the corresponding pixel of the reference image basedon the synthetic ratio; wherein computing the contrast value of thetarget pixel comprises, within an area including the target pixel,computing a maximum value of a difference between an average value ofone of luminance and brightness within the area, and one of luminanceand brightness of each pixel, as the contrast value of the target pixel.14. A computer-readable recording device having an image processingprogram coded and recorded thereon in a computer-readable format forcontrolling an image processing device to perform synthesis processingwith a base image and at least one reference image to generate asynthetic image with a smaller amount of noise than the base image, saidprogram controlling the image processing device to perform operationscomprising: computing a motion vector between the base image and thereference image; performing a motion compensation to align the referenceimage with the base image based on the motion vector; computing acontrast value of a target pixel for the synthesis processing in thebase image based on one of the base image and the reference image;computing a synthetic ratio between the target pixel of the base imageand a corresponding pixel corresponding to the target pixel in theprocessed reference image, in response to the computed contrast value ofthe target pixel; synthesizing the target pixel of the base image andthe corresponding pixel of the reference image based on the syntheticratio; and computing a reliability of the motion compensation for thetarget pixel in response to the computed contrast value of the targetpixel; wherein the synthetic ratio is computed in response to thecomputed reliability; and wherein computing the reliability comprises:computing one of a dissimilarity and a similarity between a base areaincluding the target pixel of the base image, and a reference areacorresponding to the base area within the reference image processed bythe motion compensation, performing one of a correction to reduce thecomputed dissimilarity and a correction to increase the computedsimilarity, in response to the computed contrast value of the targetpixel; and calculating the reliability such that the reliability becomeshigher as the corrected dissimilarity becomes smaller or as thecorrected similarity becomes larger; wherein correction is performedsuch that one of the dissimilarity is reduced more or the similarity isincreased more as the contrast value of the target pixel becomes higher,when the contrast value of the target pixel is within a range from afirst threshold value to a second threshold value; and whereincorrection is performed such that one of the dissimilarity and thesimilarity is corrected with a second correction amount independent fromthe contrast value, when the contrast value of the target pixel is equalto or more than the second threshold value.
 15. A computer-readablerecording device having an image processing program coded and recordedthereon in a computer-readable format for controlling an imageprocessing device to perform synthesis processing with a base image andat least one reference image to generate a synthetic image with asmaller amount of noise than the base image, said program controllingthe image processing device to perform operations comprising: computinga motion vector between the base image and the reference image;performing a motion compensation to align the reference image with thebase image based on the motion vector; computing a contrast value of atarget pixel for the synthesis processing in the base image based on oneof the base image and the reference image; computing a synthetic ratiobetween the target pixel of the base image and a corresponding pixelcorresponding to the target pixel in the processed reference image, inresponse to the computed contrast value of the target pixel;synthesizing the target pixel of the base image and the correspondingpixel of the reference image based on the synthetic ratio; and computinga reliability of the motion compensation for the target pixel inresponse to the computed contrast value of the target pixel; wherein thesynthetic ratio is computed in response to the computed reliability; andwherein computing the reliability comprises: setting respective largersizes of a base area including the target pixel in the base image and areference area corresponding to the base area within the reference imageprocessed by the motion compensation, as the contrast value of thetarget pixel becomes higher, computing one of a dissimilarity and asimilarity between the base area and the reference area, and calculatingthe reliability such that the reliability becomes higher as the computeddissimilarity becomes smaller or as the computed similarity becomeslarger.
 16. A computer-readable recording device having an imageprocessing program coded and recorded thereon in a computer-readableformat for controlling an image processing device to perform synthesisprocessing with a base image and at least one reference image togenerate a synthetic image with a smaller amount of noise than the baseimage, said program controlling the image processing device to performoperations comprising: computing a motion vector between the base imageand the reference image; performing a motion compensation to align thereference image with the base image based on the motion vector;computing a contrast value of a target pixel for the synthesisprocessing in the base image based on one of the base image and thereference image; computing a synthetic ratio between the target pixel ofthe base image and a corresponding pixel corresponding to the targetpixel in the processed reference image, in response to the computedcontrast value of the target pixel; synthesizing the target pixel of thebase image and the corresponding pixel of the reference image based onthe synthetic ratio; and computing a reliability of the motioncompensation for the target pixel in response to the computed contrastvalue of the target pixel; wherein the synthetic ratio is computed inresponse to the computed reliability; and wherein computing thereliability comprises: filtering a base area and a reference area with alow-pass filter, the base area including the target pixel of the baseimage, and the reference area corresponding to the base area within thereference image processed by the motion compensation; computing one of adissimilarity and a similarity between the base area and the referencearea after filtering with the low-pass filter; calculating thereliability such that the reliability becomes higher as the computeddissimilarity becomes smaller or as the computed similarity becomeslarger; and setting a higher strength of the low-pass filter as thecontrast value becomes higher.